Triple
T16043860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GM B-O-P |
E389164
|
entity |
| Predicate | brandGroupType |
P67912
|
FINISHED |
| Object | mid-priced GM brands |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: mid-priced GM brands | Statement: [GM B-O-P, brandGroupType, mid-priced GM brands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandGroupType Context triple: [GM B-O-P, brandGroupType, mid-priced GM brands]
-
A.
brandSegment
Indicates the specific market segment or customer group that a brand is targeted toward or associated with.
-
B.
brandAssociationType
Indicates the specific nature of the relationship or association that exists between a brand and another entity (such as a product, organization, or campaign).
-
C.
manufacturerGroup
Indicates that multiple manufacturers are associated together as a single group or consortium for a shared purpose or classification.
-
D.
hasBrandType
chosen
Indicates that an entity is associated with or categorized under a particular brand type or classification.
-
E.
sponsorBrandType
Indicates the type or category of brand that is acting as a sponsor in the relationship.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1ff63edb0819092cbb671967bbdcd |
completed | April 17, 2026, 9:37 a.m. |
| PD | Predicate disambiguation | batch_69e1826f34c081908005bb736f1c485d |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.